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Extended twosStage designs for environmental research

F, Sera1; A, Vicedo-Cabrera1; B, Armstrong1; A, Gasparrini1; the MCC Collaborative Research Network

Environmental Epidemiology: October 2019 - Volume 3 - Issue - p 132
doi: 10.1097/01.EE9.0000607192.66852.26
Abstracts of the 2019 Annual Conference of the International Society for Environmental Epidemiology, August 25-28 2019, Utrecht, the Netherlands

1London School of Hygiene & Tropical Medicine

This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0, where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially.

PDS 69: Methods and statistics, Johan Friso Foyer, Floor 1, August 26, 2019, 4:30 PM - 5:30 PM

Background/Aim: Two-stage analyses are widely applied in environmental research to investigate short-term effects of environmental stressors. The standard design involves first-stage models to derive single association estimates from multiple locations, and their pooling in second-stage random-effects meta-analysis. However, this approach can be limited for modern epidemiological investigations. In this contribution, we propose an extended two-stage framework that allows the definition of more flexible multi-location designs for environmental studies.

Methods: The extended two-stage framework is based on newly developed meta-analytical models that can incorporate multiple hierarchical levels and repeated location-specific estimates. This allows consideration of additional levels of spatial clustering, the estimation of associations at different times or for different groups, and the analysis of effect modification by location-specific characteristics varying both in time and in space. Applications are facilitated by the implementation of the meta-analytical models in the new R package mixmeta.

Applications: The extended framework is illustrated in four applications using the Multi-Country Multi-City (MCC) database, including time-series data for 633 locations in 34 countries in the period 1972-2017. First, a hierarchical two-stage design was defined to estimate pooled temperature-mortality associations with nested levels of country/location random effects, borrowing information across multiple levels. Second, first-stage models were repeated in sub-periods and the estimates were pooled in multivariate longitudinal meta-analyses to examine location and country-specific variations in temperature-mortality risks. Third, varying effects by age were investigated through multivariate dose-response meta-regression models that allow the pooling of repeated estimates for different age groups across locations and countries. Fourth, effect modification by air conditioning in heat-related risks was assessed in multivariate longitudinal meta-regressions that account for both geographical and temporal differences in air conditioning prevalence.

Conclusion: These applications demonstrate the advantages of the extended two-stage framework and its software implementation for developing flexible and innovative study designs in environmental epidemiological studies.

Copyright © 2019 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of Environmental Epidemiology. All rights reserved.